The Nov. Jobs Report was Strong Last Month.

What Happened This Month with the Nov. JOLTS Report?


The Monthly Employment Situation Report is a market mover. The report is created using two different data sets: the Current Population Survey (CPS) jobs and unemployment data and the Current Employment Statistics (CES) worker and wages data. It doesn't break down the data at the State Level. Today's November State Employment and Unemployment Report  does break it down by state.


This is what has been previously discussed:

  • We added 504,000 non-seasonally adjusted private sector workers this month. We added 266,000 seasonally adjusted Non-Farm Payroll Workers. We added 254,000 SA Private Sector Workers. This was covered in "Nov. Jobs Report: Surprise, Surprise."
  • We had a record number of private sector workers earning record setting hourly wages during November. This was covered in the article "November Jobs Report: Manufacturing Success."
  • President Trump has added more full-time jobs than his predecessors. He has also added workers in every sector of the workforce, something his predecessors cannot say.This was covered in "Five President at 34 Months: Monster Month."
  • Women and Men were at record levels of jobs during October. What Happened this month? This was covered in "Record Nov. Jobs for Men and Women.
  • "Where are the Workers in 17 Swung States" examined the Regional and State Employment and Unemployment data and found that  November was a strong jobs and workers month. Four states that have seen worker growth in every sector of the Economy since November 2016, sixteen of the seventeen state have seen growth in the Manufacturing sector, Nevada, Arizona, Utah, South Carolina and Georgia led with the highest growth rates, while Arizona, Georgia, Illinois, Nevada and New Jersey added the most workers.

Another report on the November Jobs data was released last week, the Job Opening and Labor Turnover Survey data. Where were the Job openings, Hires, Quits, and Total Separations?


Same Story Month to Month. The same four sectors had the most Job Openings, Hires, Quits and Separations: Education and Health Services (EHS,) Trade, Transportation and Utilities (TTU,) Professional Business Services (PBS,) and Education and Health Services (EHS)

  • Job Openings: EHS, TTU, PBS, EHS
  • Hires, TTU, PBS, LAH, EHS
  • Quits TTU, LAH, PBS, EHS
  • Separations: TTU, PBS, LAH, EHS

The data changes month to month. The hierarchy changes month to month. These four categories jockey for position each month.  Additional graphics can be found here.


Record November Level  of Quits this December. There were some in the Legacy Media expressing concern regarding the dropping level of seasonally adjusted job openings. Seasonal factors change by category, month, and year. This is often ignored elsewhere.

  • Record November Quits: 5.751 Million this November, compared with 2.693 million November 2018 and 2.505 million November 2017.
  • Record November level of total Separations at 4.745 million. This compares with 4.713 million during November 2018 and 4.547 million during November 2006, over a decade ago.
  • Second Highest Ever November Job Opening Level at 5.751 million. Last year the November opening level was 6.656 million. The 2017 level was 5.365 million.
  • Second Highest Ever November level of Hires at 5.107 million. This compares with 5.113 million during November 2018 and 4.804 million during November 2017. Note that we were just 6,000 hires away from the record that was set last year. The graphics for these data points can be found here.


The JOLTS data is always one month and one week behind the Employment Situation data. This month we received the December Jobs Report and the November JOLTS data. The job report data is a combination of two data sets, the Current Population Survey (CPS) jobs and unemployment data and the Current Employment Statistics (CES) worker and wages data. All of this data has seasonally adjusted data and non-seasonally adjusted data. They have different sample sizes and are measuring different things. This was remarkable JOLTS data.


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